The emergence of artificial intelligence (AI) has continually reshaped a range of sectors across the business world.
However, the convenience of AI needs to be balanced against the environmental consequences and the unplanned actions that often arise from the unnecessary usage of hardware, energy, and model training. With the knowledge of digital technologies and a robust foundation to support sustainable development, chief information officers (CIOs) should consider implementing AI initiatives.
According to a survey by Gartner, it is evident that environmental issues are a top priority, and tech companies need to focus on eliminating these issues. Consequently, the CIOs are under pressure from executives, stakeholders, and regulators to initiate and reinforce sustainability programs for IT.
Thus, the combination of adopting AI and environmental sustainability requires proactive strategies that will transform your business. This article describes a framework for the adoption of green algorithms that CIOs can implement in IT organizations to support sustainable development.
Define Sustainability Goals
A well-defined sustainability objective acts as a roadmap for guiding and developing AI-driven solutions that any organization will implement. This objective will help you to reduce waste, achieve carbon neutralization, and engage in socially beneficial activities for your organization. CIOs can refer to the United Nations’ Sustainable Development Goals (SDGs) to identify sustainability goals. Project management software such as Asana has inbuilt tailored sustainable metrics that can help you plan your OKRs (objectives and key results) based on your team and organization’s vision and goals.
The project managers and CIOs must focus on building a strong centralized data foundation to ensure that the green algorithms are functioning optimally when integrated into a project. To make sustainably sound decisions for your organization, you and your team must focus on developing green algorithms that have comprehensive and real-time data. A project manager can also use data management platforms or data lakes to store sustainability attributes such as waste emissions, energy usage, and emissions.
For effective project management, project managers must opt for customizing their green algorithms, as generic algorithms cannot address sustainability challenges effectively. Hence, project managers can opt for pre-built algorithms to meet their sustainability objectives, as mentioned earlier.
AI comes with its cons for environmental sustainability but has the potential to create green footprints that can boost many sustainable initiatives, which can only be achieved if businesses, their CIOs, and project managers proactively strategize, initiate, and implement AI initiatives that help achieve the SDGs of their organizations.
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